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ABSTRACT: Background
The outcomes of patients undergoing esophagogastroduodenoscopy (EGD) in the intensive care unit (ICU) for upper gastrointestinal bleeding (UGIB) are not well described. Our aims were to determine predictors of 30-day mortality and endoscopic intervention, and assess the utility of existing clinical-prediction tools for UGIB in this population.Methods
Patients hospitalized in an ICU between 2008 and 2015 who underwent EGD were identified using a validated, machine-learning algorithm. Logistic regression was used to determine factors associated with 30-day mortality and endoscopic intervention. Area under receiver-operating characteristics (AUROC) analysis was used to evaluate established UGIB scoring systems in predicting mortality and endoscopic intervention in p
SUBMITTER: Rao VL
PROVIDER: S-EPMC7434581 | biostudies-literature | 2020 Aug
REPOSITORIES: biostudies-literature